2026-09-19T10:43:51Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/367712026-06-06T01:04:31Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Glen L. Urban.
Narang, Aman
Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2007-03-12T17:52:16Z
2007-03-12T17:52:16Z
2006
2006
http://hdl.handle.net/1721.1/36771
78926055
Thesis (M. Eng. and S.B.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.
Includes bibliographical references (leaf 52).
As eCommerce becomes more prevalent, good site design that can cater to users with different backgrounds and experience becomes increasingly important. While many web based applications provide customized content, these systems do not adapt and provide a customized user experience as one navigates the site. Our research investigates customizing web applications to fit individual decision styles by morphing user experience based on revealed clicks, search history, and the navigation path through the site. By using a Bayesian update algorithm to update our assessment of a user's preferred interface, our application creates a customized user experience that is best suited for their personality and learning style.
by Aman Narang.
M.Eng.
S.B.
52 leaves
eng
Massachusetts Institute of Technology
M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
http://dspace.mit.edu/handle/1721.1/7582
Electrical Engineering and Computer Science.
An eCommerce platform for customized page design and content delivery
Thesis
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